Prospective methodologies in hybrid renewable energy systems for energy prediction using artificial neural networks

MM Rahman, M Shakeri, SK Tiong, F Khatun, N Amin… - Sustainability, 2021 - mdpi.com
This paper presents a comprehensive review of machine learning (ML) based approaches,
especially artificial neural networks (ANNs) in time series data prediction problems …

Review of mapping analysis and complementarity between solar and wind energy sources

R Pedruzzi, AR Silva, TS dos Santos, AC Araujo… - Energy, 2023 - Elsevier
This review aims to identify the available methodologies, data, and techniques for mapping
the potential of solar and wind energy and its complementarity and to provide significant …

The High-Resolution Rapid Refresh (HRRR): An hourly updating convection-allowing forecast model. Part I: Motivation and system description

DC Dowell, CR Alexander, EP James… - Weather and …, 2022 - journals.ametsoc.org
Abstract The High-Resolution Rapid Refresh (HRRR) is a convection-allowing
implementation of the Advanced Research version of the Weather Research and …

[HTML][HTML] On bridging a modeling scale gap: Mesoscale to microscale coupling for wind energy

SE Haupt, B Kosovic, W Shaw, LK Berg… - Bulletin of the …, 2019 - journals.ametsoc.org
Accurately representing flow across the mesoscale to the microscale is a persistent
roadblock for completing realistic microscale simulations. The science challenges that must …

Representation of boundary-layer processes in numerical weather prediction and climate models

JM Edwards, ACM Beljaars, AAM Holtslag… - Boundary-Layer …, 2020 - Springer
Boundary-layer schemes are essential components of numerical weather-forecasting and
climate models. From simple beginnings 50 years ago, they have grown in sophistication …

[HTML][HTML] Temporal collaborative attention for wind power forecasting

Y Hu, H Liu, S Wu, Y Zhao, Z Wang, X Liu - Applied Energy, 2024 - Elsevier
Wind power serves as a clean and sustainable form of energy. However, its generation is
fraught with variability and uncertainty, owing to the stochastic and dynamic characteristics …

[PDF][PDF] Accurate weather forecasting with dominant gradient boosting using machine learning

S Babu Nuthalapati, A Nuthalapati - Int. J. Sci. Res. Arch, 2024 - researchgate.net
This Paper examines the interesting topic of weather forecasting using ML. From kaggle.
com, there is an extensive list of daily weather records for a Seattle dataset. In this chapter …

[HTML][HTML] The second wind forecast improvement project (WFIP2): Observational field campaign

JM Wilczak, M Stoelinga, LK Berg… - Bulletin of the …, 2019 - journals.ametsoc.org
The Second Wind Forecast Improvement Project (WFIP2): Observational Field Campaign in:
Bulletin of the American Meteorological Society Volume 100 Issue 9 (2019) Jump to …

[HTML][HTML] The second wind forecast improvement project (wfip2): general overview

WJ Shaw, LK Berg, J Cline, C Draxl… - Bulletin of the …, 2019 - journals.ametsoc.org
Akish, E., L. Bianco, IV Djalalova, JM Wilczak, J. Olson, J. Freedman, C. Finley, and J. Cline,
2019: Measuring the impact of additional instrumentation on the skill of numerical weather …

[HTML][HTML] The December 2021 Marshall Fire: Predictability and gust forecasts from operational models

RG Fovell, MJ Brewer, RJ Garmong - Atmosphere, 2022 - mdpi.com
We analyzed meteorological conditions that occurred during the December 2021 Boulder,
Colorado, downslope windstorm. This event is of particular interest due to the ignition and …